AI Literacy, Readiness, and Ecosystem Support in Student AI Adoption - Agung Stefanus Kembau; I Gede Wisnu Satria Chandra Putra; Felliks Feiters Tampinongkol; Derick Raditya (Universitas Bunda Mulia, 2025)
Artificial intelligence has rapidly become a routine part of students’ academic workflows, reshaping how they learn, create, and complete tasks. This study examines the extent to which AI literacy and AI readiness influence AI adoption among university students, and whether an AI-supportive learning climate strengthens these relationships. Using data from 187 students in Jakarta, the research employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate both direct and moderating effects. The findings show that AI readiness is the strongest predictor of AI adoption, highlighting the importance of psychological preparedness, confidence, and openness toward AI tools. AI literacy also demonstrates a significant positive effect, suggesting that conceptual understanding, functional skills, and critical evaluation abilities are essential to meaningful AI integration. Furthermore, an AI-supportive learning climate positively moderates both relationships, indicating that institutional and instructional encouragement amplify the translation of literacy and readiness into actual adoption behavior. To enrich interpretation, the study also presents descriptive evidence of students’ primary purposes for using AI, which are largely tied to core academic activities such as completing assignments and understanding difficult concepts. Despite its contributions, the study is limited by its cross-sectional design, reliance on self-reported data, and focus on an urban sample. These limitations restrict causal inference and may not fully capture the diverse conditions across Indonesian higher education. Future research should incorporate longitudinal designs, broader regional samples, and mixed-method approaches to capture evolving patterns of AI engagement. Overall, the study contributes to a deeper understanding of how individual capabilities and supportive environments jointly shape AI adoption in higher education